How to prioritise villages for a WASH baseline survey

Every baseline survey starts with the same problem. You've got a district brief, a budget that covers maybe sixty villages this quarter, and a settlement list with four hundred names on it. Someone always asks "which villages do we visit first," and the honest answer is usually "whichever ones the last NGO already covered," because that's the data you have.

That's backwards. Here's a way to build a priority list that holds up when your donor asks why you went where you went.

Start with what you can rule out, not what you can confirm

The instinct is to rank villages by need: worst water access first, worst sanitation first. That sounds right, but need is exactly what you don't know yet, that's the whole point of the baseline. What you can rank, before a single field visit, is exposure and plausibility.

Pull together whatever you already have: the last census round, any handpump inventory from a previous programme, district health office reports on diarrhoeal disease, and population estimates by settlement. None of this is current or complete, but it tells you which villages are large enough to matter, which ones sit in flood-prone or drought-prone zones, and which ones haven't had a water point built or repaired in the time anyone can remember. That gets your four hundred down to maybe a hundred and fifty worth a closer look.

Then split that hundred and fifty by travel cost, not need. A village forty minutes off the main road costs your team the same fuel and daylight as three villages strung along it. If your remaining budget is really a budget of field-days, route efficiency decides half your order before a single tap test happens.

Build the short list from gaps, not guesses

The part that actually separates a rapid needs assessment from a slow one is how you handle the villages with no recent record at all. Those are usually the ones everyone skips, because nobody wants to send a team somewhere with zero baseline to compare against. But a settlement with no water point recorded anywhere in the last five years is either genuinely uncovered or just never got surveyed. You can't tell the difference from a spreadsheet.

This is where a recent overhead pass of the district earns its keep. A single annual satellite pass, read against what you already know, turns "no record" into "no visible borehole, tank stand, or latrine block in this settlement as of this year" or "there's clearly infrastructure here that nobody logged." That distinction changes a village's place on your list more than almost anything else you can pull from an office desk. It's the difference between sending a team to confirm a gap and sending a team to find out whether there was ever a gap to begin with.

Once you've got that overlay, the short list almost writes itself: settlements above a size threshold, with no confirmed water point, no confirmed latrine coverage, and reasonable road access, go to the top. Settlements with visible infrastructure but an uncertain condition go second, since you still need boots on the ground to check whether that borehole runs dry three months a year. Everything else waits for the next funding round.

Write the reasoning down as you go, not after. A district coordinator or a donor reviewing the survey plan six months later will ask why village A got a visit before village B, and "it looked like a gap on the latest pass and it's on the main route" is a better answer than "we always do the accessible ones first."

Sanitation Mapping builds that kind of point inventory from one annual VHR pass over your district, located and dated, so the "no record" villages on your list stop being a guess before your team ever leaves the office.

Prioritising villages for a baseline is really a triage exercise disguised as a data problem. Get the office-side filtering right and the field days go where they need to.